Sanghamitra Dutta

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 57

Top Topics

Matrix Multiplication

Monetary Policy

Hypothesis Test

Top Venues

IEEE Trans. Inf. Theory

Publications

Faisal Hamman, Sanghamitra Dutta
Demystifying Local & Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition. ICLR (2024)
Pasan Dissanayake, Sanghamitra Dutta
Model Reconstruction Using Counterfactual Explanations: Mitigating the Decision Boundary Shift. CoRR (2024)
Barproda Halder, Faisal Hamman, Pasan Dissanayake, Qiuyi Zhang, Ilia Sucholutsky, Sanghamitra Dutta
Quantifying Spuriousness of Biased Datasets Using Partial Information Decomposition. CoRR (2024)
Faisal Hamman, Erfaun Noorani, Saumitra Mishra, Daniele Magazzeni, Sanghamitra Dutta
Robust Algorithmic Recourse Under Model Multiplicity With Probabilistic Guarantees. IEEE J. Sel. Areas Inf. Theory 5 (2024)
Faisal Hamman, Pasan Dissanayake, Saumitra Mishra, Freddy Lécué, Sanghamitra Dutta
Quantifying Prediction Consistency Under Model Multiplicity in Tabular LLMs. CoRR (2024)
Akshaj Kumar Veldanda, Ivan Brugere, Sanghamitra Dutta, Alan Mishler, Siddharth Garg
Hyper-parameter Tuning for Fair Classification without Sensitive Attribute Access. Trans. Mach. Learn. Res. 2024 (2024)
Faisal Hamman, Sanghamitra Dutta
A Unified View of Group Fairness Tradeoffs Using Partial Information Decomposition. CoRR (2024)
Shubham Sharma, Sanghamitra Dutta, Emanuele Albini, Freddy Lécué, Daniele Magazzeni, Manuela Veloso
REFRESH: Responsible and Efficient Feature Reselection Guided by SHAP Values. CoRR (2024)
Shubham Sharma, Sanghamitra Dutta, Emanuele Albini, Freddy Lécué, Daniele Magazzeni, Manuela Veloso
REFRESH: Responsible and Efficient Feature Reselection guided by SHAP values. AIES (2023)
Faisal Hamman, Jiahao Chen, Sanghamitra Dutta
Can Querying for Bias Leak Protected Attributes? Achieving Privacy With Smooth Sensitivity. FAccT (2023)
Faisal Hamman, Erfaun Noorani, Saumitra Mishra, Daniele Magazzeni, Sanghamitra Dutta
Robust Counterfactual Explanations for Neural Networks With Probabilistic Guarantees. CoRR (2023)
Sanghamitra Dutta, Faisal Hamman
A Review of Partial Information Decomposition in Algorithmic Fairness and Explainability. Entropy 25 (5) (2023)
Faisal Hamman, Sanghamitra Dutta
Demystifying Local and Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition. CoRR (2023)
Akshaj Kumar Veldanda, Ivan Brugere, Jiahao Chen, Sanghamitra Dutta, Alan Mishler, Siddharth Garg
Fairness via In-Processing in the Over-parameterized Regime: A Cautionary Tale with MinDiff Loss. Trans. Mach. Learn. Res. 2023 (2023)
Faisal Hamman, Erfaun Noorani, Saumitra Mishra, Daniele Magazzeni, Sanghamitra Dutta
Robust Counterfactual Explanations for Neural Networks With Probabilistic Guarantees. ICML (2023)
Sahil Garg, Sanghamitra Dutta, Mina Dalirrooyfard, Anderson Schneider, Yuriy Nevmyvaka
In- or out-of-distribution detection via dual divergence estimation. UAI (2023)
Akshaj Kumar Veldanda, Ivan Brugere, Sanghamitra Dutta, Alan Mishler, Siddharth Garg
Hyper-parameter Tuning for Fair Classification without Sensitive Attribute Access. CoRR (2023)
Akshaj Kumar Veldanda, Ivan Brugere, Jiahao Chen, Sanghamitra Dutta, Alan Mishler, Siddharth Garg
Fairness via In-Processing in the Over-parameterized Regime: A Cautionary Tale. CoRR (2022)
Faisal Hamman, Jiahao Chen, Sanghamitra Dutta
Can Querying for Bias Leak Protected Attributes? Achieving Privacy With Smooth Sensitivity. CoRR (2022)
Sanghamitra Dutta, Jason Long, Saumitra Mishra, Cecilia Tilli, Daniele Magazzeni
Robust Counterfactual Explanations for Tree-Based Ensembles. ICML (2022)
Puneet Mathur, Atula Tejaswi Neerkaje, Malika Chhibber, Ramit Sawhney, Fuming Guo, Franck Dernoncourt, Sanghamitra Dutta, Dinesh Manocha
MONOPOLY: Financial Prediction from MONetary POLicY Conference Videos Using Multimodal Cues. ACM Multimedia (2022)
Sanghamitra Dutta, Praveen Venkatesh, Pulkit Grover
Quantifying Feature Contributions to Overall Disparity Using Information Theory. CoRR (2022)
Sanghamitra Dutta, Jason Long, Saumitra Mishra, Cecilia Tilli, Daniele Magazzeni
Robust Counterfactual Explanations for Tree-Based Ensembles. CoRR (2022)
Chenyu Jiang, Bowen Wu, Sanghamitra Dutta, Pulkit Grover
An Information-Theoretic Measure for Enabling Category Exemptions with an Application to Filter Bubbles. BIAS (2021)
Sanghamitra Dutta, Praveen Venkatesh, Piotr Mardziel, Anupam Datta, Pulkit Grover
Fairness Under Feature Exemptions: Counterfactual and Observational Measures. IEEE Trans. Inf. Theory 67 (10) (2021)
Saumitra Mishra, Sanghamitra Dutta, Jason Long, Daniele Magazzeni
A Survey on the Robustness of Feature Importance and Counterfactual Explanations. CoRR (2021)
Sanghamitra Dutta, Jianyu Wang, Gauri Joshi
Slow and Stale Gradients Can Win the Race. IEEE J. Sel. Areas Inf. Theory 2 (3) (2021)
Praveen Venkatesh, Sanghamitra Dutta, Neil Mehta, Pulkit Grover
Can Information Flows Suggest Targets for Interventions in Neural Circuits? CoRR (2021)
Sanghamitra Dutta, Liang Ma, Tanay Kumar Saha, Di Lu, Joel R. Tetreault, Alex Jaimes
GTN-ED: Event Detection Using Graph Transformer Networks. CoRR (2021)
Praveen Venkatesh, Sanghamitra Dutta, Neil Mehta, Pulkit Grover
Can Information Flows Suggest Targets for Interventions in Neural Circuits? NeurIPS (2021)
Sanghamitra Dutta, Praveen Venkatesh, Piotr Mardziel, Anupam Datta, Pulkit Grover
An Information-Theoretic Quantification of Discrimination with Exempt Features. AAAI (2020)
Sanghamitra Dutta, Praveen Venkatesh, Piotr Mardziel, Anupam Datta, Pulkit Grover
Fairness Under Feature Exemptions: Counterfactual and Observational Measures. CoRR (2020)
Sanghamitra Dutta, Jianyu Wang, Gauri Joshi
Slow and Stale Gradients Can Win the Race. CoRR (2020)
Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush R. Varshney
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing. ICML (2020)
Sanghamitra Dutta, Haewon Jeong, Yaoqing Yang, Viveck R. Cadambe, Tze Meng Low, Pulkit Grover
Addressing Unreliability in Emerging Devices and Non-von Neumann Architectures Using Coded Computing. Proc. IEEE 108 (8) (2020)
Sanghamitra Dutta, Mohammad Fahim, Farzin Haddadpour, Haewon Jeong, Viveck R. Cadambe, Pulkit Grover
On the Optimal Recovery Threshold of Coded Matrix Multiplication. IEEE Trans. Inf. Theory 66 (1) (2020)
Praveen Venkatesh, Sanghamitra Dutta, Pulkit Grover
Information Flow in Computational Systems. IEEE Trans. Inf. Theory 66 (9) (2020)
Praveen Venkatesh, Sanghamitra Dutta, Pulkit Grover
How else can we define Information Flow in Neural Circuits? ISIT (2020)
Sanghamitra Dutta, Viveck R. Cadambe, Pulkit Grover
"Short-Dot": Computing Large Linear Transforms Distributedly Using Coded Short Dot Products. IEEE Trans. Inf. Theory 65 (10) (2019)
Sanghamitra Dutta, Ziqian Bai, Tze Meng Low, Pulkit Grover
CodeNet: Training Large Scale Neural Networks in Presence of Soft-Errors. CoRR (2019)
Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush R. Varshney
An Information-Theoretic Perspective on the Relationship Between Fairness and Accuracy. CoRR (2019)
Praveen Venkatesh, Sanghamitra Dutta, Pulkit Grover
Information Flow in Computational Systems. CoRR (2019)
Praveen Venkatesh, Sanghamitra Dutta, Pulkit Grover
How should we define Information Flow in Neural Circuits? ISIT (2019)
Sanghamitra Dutta, Gauri Joshi, Soumyadip Ghosh, Parijat Dube, Priya Nagpurkar
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD. AISTATS (2018)
Sanghamitra Dutta, Ziqian Bai, Haewon Jeong, Tze Meng Low, Pulkit Grover
A Unified Coded Deep Neural Network Training Strategy based on Generalized PolyDot codes. ISIT (2018)
Sanghamitra Dutta, Ziqian Bai, Haewon Jeong, Tze Meng Low, Pulkit Grover
A Unified Coded Deep Neural Network Training Strategy Based on Generalized PolyDot Codes for Matrix Multiplication. CoRR (2018)
Utsav Sheth, Sanghamitra Dutta, Malhar Chaudhari, Haewon Jeong, Yaoqing Yang, Jukka Kohonen, Teemu Roos, Pulkit Grover
An Application of Storage-Optimal MatDot Codes for Coded Matrix Multiplication: Fast k-Nearest Neighbors Estimation. IEEE BigData (2018)
Utsav Sheth, Sanghamitra Dutta, Malhar Chaudhari, Haewon Jeong, Yaoqing Yang, Jukka Kohonen, Teemu Roos, Pulkit Grover
An Application of Storage-Optimal MatDot Codes for Coded Matrix Multiplication: Fast k-Nearest Neighbors Estimation. CoRR (2018)
Sanghamitra Dutta, Gauri Joshi, Soumyadip Ghosh, Parijat Dube, Priya Nagpurkar
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD. CoRR (2018)
Sanghamitra Dutta, Mohammad Fahim, Farzin Haddadpour, Haewon Jeong, Viveck R. Cadambe, Pulkit Grover
On the Optimal Recovery Threshold of Coded Matrix Multiplication. CoRR (2018)
Sanghamitra Dutta, Viveck R. Cadambe, Pulkit Grover
Coded convolution for parallel and distributed computing within a deadline. CoRR (2017)
Sanghamitra Dutta, Viveck R. Cadambe, Pulkit Grover
Coded convolution for parallel and distributed computing within a deadline. ISIT (2017)
Mohammad Fahim, Haewon Jeong, Farzin Haddadpour, Sanghamitra Dutta, Viveck R. Cadambe, Pulkit Grover
On the optimal recovery threshold of coded matrix multiplication. Allerton (2017)
Sanghamitra Dutta, Viveck R. Cadambe, Pulkit Grover
"Short-Dot": Computing Large Linear Transforms Distributedly Using Coded Short Dot Products. CoRR (2017)
Sanghamitra Dutta, Pulkit Grover
Adaptivity provably helps: Information-theoretic limits on l0 cost of non-adaptive sensing. ISIT (2016)
Sanghamitra Dutta, Pulkit Grover
Adaptivity provably helps: information-theoretic limits on $l_0$ cost of non-adaptive sensing. CoRR (2016)
Sanghamitra Dutta, Viveck R. Cadambe, Pulkit Grover
Short-Dot: Computing Large Linear Transforms Distributedly Using Coded Short Dot Products. NIPS (2016)
Sanghamitra Dutta, Arijit De
LAMP: A Locally Adapting Matching Pursuit Framework for Group Sparse Signatures in Ultra-Wide Band Radar Imaging. CoRR (2014)